Pre-positioning pre-stored content in a content distribution system

ABSTRACT

A method for execution by one or more processing modules of one or more computing devices of a dispersed storage network (DSN), the method begins by selecting a plurality of network edge units for staging public pillar encoded data slices. The method continues by identifying target content for partial download to the plurality of network edge units. The method continues by identifying public pillars corresponding to the target content for partial download. The method continues by determining a partial downloading schedule for sending public pillar encoded data slices, corresponding to the public pillars, to each network edge unit of the plurality of network edge units and facilitating partial downloading of the target content by facilitating sending of the public pillar encoded data slices to each network edge unit of the plurality of network edge units.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation-in-part of U.S. Utility applicationSer. No. 15/190,925, entitled “WIRELESSLY COMMUNICATING A DATA FILE”,filed Jun. 23, 2016, which is a continuation of U.S. Utility applicationSer. No. 13/647,528, entitled “WIRELESSLY COMMUNICATING A DATA FILE”,filed Oct. 9, 2012, now U.S. Pat. No. 9,400,714, which is acontinuation-in-part of U.S. Utility patent application Ser. No.13/464,166, entitled “DISTRIBUTING MULTI-MEDIA CONTENT TO A PLURALITY OFPOTENTIAL ACCESSING DEVICES,” filed MAY 4, 2012, now U.S. Pat. No.8,762,479, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S.Provisional Application No. 61/493,825, entitled “ACCESSING DATA IN ADISPERSED STORAGE NETWORK,” filed Jun. 6, 2011.

U.S. Utility patent application Ser. No. 13/647,528 also claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.61/554,152, entitled “COMMUNICATING DATA UTILIZING DATA DISPERSAL,”filed Nov. 1, 2011, which is incorporated herein by reference in itsentirety and made part of the present U.S. Utility Patent Applicationfor all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of another embodiment of a computingsystem in accordance with the invention;

FIG. 9A is a flowchart illustrating an example of staging content fordownloading in accordance with the invention; and

FIG. 9B is a flowchart illustrating an example of staging content fordownloading in accordance with the invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30,32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-9B. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSTN memory 22for a user device, a group of devices, or for public access andestablishes per vault dispersed storage (DS) error encoding parametersfor a vault. The managing unit 18 facilitates storage of DS errorencoding parameters for each vault by updating registry information ofthe DSN 10, where the registry information may be stored in the DSNmemory 22, a computing device 12-16, the managing unit 18, and/or theintegrity processing unit 20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generateper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSTN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (10)controller 56, a peripheral component interconnect (PCI) interface 58,an 10 interface module 60, at least one 10 device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the

IO device interface module 62 and/or the memory interface modules 66-76may be collectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R)of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a computingsystem. Such a computing system includes a plurality of contentproviders 1-C, a dispersed storage (DS) processing unit 16, a network24, a dispersed storage network (DSN) memory 22, a wireless controller102, a base station 108, a wireless router 104, a distribution server106, a user device 12, a wireless transceiver 112, a low tier userdevice 114, and a wireless user device 110. Such a DSN memory 22includes a plurality of DS units 36. Such a wireless controller,wireless router, distribution server, user device, and a wireless userdevice may include a slice memory (SM) 116. Such a slice memory includesa temporary slice memory 118 (e.g., for storing encoded data slices on atemporary basis) and a non-temporary slice memory 120 (e.g., for storingencoded data slices on a non-temporary basis).

Such a content provider 1-C may aggregate and store content 122 fordistribution to one or more of the user devices (e.g., low tier userdevice 114, user device 12, wireless user device 110). Such content 122includes one or more of multimedia, video, movies, music, audiorecordings, pictures, sound files, image files, applications, orsoftware. Such content 122 may be associated with a content descriptorincluding one or more of a content type, a genre type, an artist, amovie type, a music type, a release date, pricing information, purchaseindicator information, a demographic indicator, a favorite syndicator, aquality rating, or an industry rating. Such a descriptor may be includedwith the content 122.

Such a DS processing unit 16 ingests new content 122 by receivingcontent from the content providers 1-C, dispersed storage error encodingat least some of the content to produce slices 11, and sending slices 11to the DSN memory 22 for storage in at least some of the DS units 36.Such a DS processing unit 16 distributes content by one or more ofreceiving a content request and facilitating sending of slicesassociated with the content of the request to a requesting entity (e.g.,a user device 12); and determining target content for a user device,facilitating temporarily storing some slices (e.g., public pillarslices) associated with the target content in the user device 12, andfacilitating sending other slices (e.g., private pillar slices)associated with target content to the user device 12 when the userdevice requests the target content.

A wireless controller 102 controls base station 108 such that the basestation converts slices 11 to wide-area signals 124 for transmission toone or more wireless user devices 110. Such a base station 108 mayoperate in accordance with one or more industry standards (e.g., globalsystem for mobile communications (GSM), code division multiple access(CDMA), etc.) to transmit and receive wide-area signals. A wirelessrouter 104 converts slices 11 into local area signals 126 fortransmission to one or more wireless devices. Such a wireless router mayoperate in accordance with one or more industry standards (e.g., WIFI,Bluetooth) to transmit and receive local area signals 126. Adistribution server 106 distributes slices 11 (e.g., via a wireline orwireless connection) to one or more of the wireless transceiver 112, thelow tier user device 114, and the user device 12. Such a wirelesstransceiver 112 converts slices into local area signals 126 fortransmission to one or more wireless devices. Such a wirelesstransceiver may operate in accordance with one or more industrystandards (e.g., WIFI, Bluetooth) to transmit and receive local areasignals.

User device 12 and low tier user device 114 include wirelinecommunication capability (e.g., a wireline interface). Wireless userdevice 110 includes a wireless transceiver to communicate wide areasignals 124 and/or local area signals 126 with one or more of anotherwireless user device 110, the base station 108, the wireless router 104,and the wireless transceiver 112. Such a user device, low tier userdevice, and wireless user device communicate with the computing systemvia one or more of the base station, the wireless router, the wirelesstransceiver, the distribution server, and the network 24 to receivepublic pillar slices for at least temporary storage, request targetcontent, and receive private pillar slices for non-temporary storage.

User device 12, low tier user device 114, and wireless user device 110include DS processing which functions include one or more of temporarilystoring public pillar slices, deleting temporarily stored public pillarslices when such slices are not required, storing private pillar slices,dispersed storage error decoding slices into target content, dispersedstorage error encoding target content into slices, transcoding slicesthat were encoded with a first set of dispersal parameters into slicesencoded with a second set of dispersal parameters, determining usercontent preferences, identifying target content, facilitating requestingtarget content, facilitating sharing target content, or consuming targetcontent (e.g., playing a movie, playing a music file, etc.)

FIG. 9A is a flowchart illustrating an example of facilitating partialcontent downloading (pre-positioning). The method begins with a step 128where a processing module (e.g., of a dispersed storage (DS) processingunit, a user device) identifies target content for a user device. Such adetermination may be based on one or more of a user content preference,a new content listing message, user desired content, a user contentselection, user content selection history, a predictive algorithm, amessage, a match to a demographic fit, or content already sent. Forexample, the processing module identifies the target content when thetarget content includes music from an artist that matches an artistentry of the user content preference.

The method continues at step 130 where the processing module identifiespublic pillars corresponding to the target content for partial download.Such an identification may be based on one or more of the targetcontent, error coding parameters (e.g., a pillar width, a decodethreshold, a write threshold, a read threshold), an amount of data perpillar, a security requirement, a performance requirement,predetermination, a lookup, a pillar assignment for the user device, ora query. For example, the processing module identifies pillars 1-9 asthe public pillars corresponding to the target content when a decodethreshold is 10 and the security requirement indicates a withholdingpattern to withhold one pillar. Such a withholding pattern may indicateto withhold one or more pillars of a decode threshold number of pillars.

The method continues at step 132 where the processing module determinesa partial downloading schedule for sending public pillar encoded dataslices corresponding to the public pillars. Such a schedule may includea start time, an end time, how much of the target content to partiallydownload, a minimum download rate, an average download rate, or amaximum download rate. Such a determination may be based on one or moreof a network loading indicator, historical network loading information,the target content, the size of the target content, a size of encodeddata slices associated with the public pillars, user deviceavailability, a user device type indicator (e.g., wireless and/orwireline), or a security requirement. For example, the processing moduledetermines to start the download to a wireless user device, with amaximum download rate of 3 kilobits per second, at 3 AM and complete thedownload by 5 AM when the historical network loading informationindicates that a wireless network associated with the network typicallyhas more available capacity in this time frame and the wireless userdevice is available.

The method continues at step 134 where the processing module facilitatespartial downloading of the target content by facilitating sending of thepublic pillar encoded data slices to the user device. Such facilitationincludes at least one of retrieving of the public pillar encoded dataslices when the processing module is associated with the user device andrequesting sending of the public pillar encoded data slices when theprocessing module is associated with a DS processing unit.

In an example of operation, in step 128, a wireless user device 110operably coupled to base station 108 determines a user contentpreference and identifies target content associated with the usercontent preference. In step 130, wireless user device 110 identifiespublic pillars corresponding to the target content for a partialdownload. In step 132, wireless user device 110 determines a partialdownloading schedule (e.g., sending slices on off hours such that basestation effectiveness is not compromised) for retrieving public pillarencoded data slices corresponding to the public pillars. In step 134,wireless user device 110 facilitates partial downloading of the targetcontent by facilitating sending of the public pillar encoded data slicesto the wireless user device 110 via the wireless controller 102 and basestation 108 utilizing the wide-area signals 124. For example, thewireless user device sends a slice retrieval request to the DSN memory22, wherein the request includes a slice name associated with a publicpillar encoded data slice. Alternatively, or in addition to, the DSprocessing unit 16, user device 12 or low tier user device 114,determines the user content preference, identifies the target content,identifies the public pillars, determines the partial downloadingschedule, and facilitates partial downloading of the target content.

In the example continued, the wireless user device receives the publicpillar encoded slices, via the wide area signals, of the target contentand stores the slices in a temporary slice memory 118 of the wirelessuser device. The wireless user device determines whether the targetcontent is desired. For example, the wireless user device receives auser input that selects the target content to indicate that the targetcontent is desired target content. When the target content is desired,the wireless user device identifies one or more required private pillarsof the desired target content and requests encoded data slices (e.g.,from the DSN memory 22) corresponding to the one or more requiredprivate pillars, receives the private pillar encoded data slices via thewide area signals, stores the private pillar encoded data slices innon-temporary slice memory 120, and moves the public pillar encoded dataslices from the temporary slice memory 118 to a non-temporary slicememory 120 of the wireless user device 110.

In another example of operation, a wireless user device 110 operablycoupled to the wireless router communicates with the DSN memory 22 viathe wireless router utilizing the local area signals 126. The wirelessuser device may forward at least some of the public pillar encoded dataslices to another wireless user device operably coupled to the wirelessuser device utilizing local area signals. In yet another example ofoperation, the low tier user device 114 communicates with the DSN memory22 via the distribution server utilizing a wireline connection andfacilitates storage of public pillar encoded data slices and privatepillar encoded data slices in a slice memory of the distribution server.As such, the low tier user device accesses the slice memory of thedistribution server to consume slices as target content.

As yet another example of operation, the DS processing unit 16 selects aplurality of network edge units for staging public pillar encoded dataslices. Such a plurality of network edge units includes one or more ofthe wireless controller 102, the wireless router 104, the distributionserver 106, a user device 12, and a wireless user device 110. The DSprocessing unit 16 identifies target content for partial download to theplurality of network edge units. The DS processing unit 16 identifiespublic pillars corresponding to the target content for partial downloadand determines a partial downloading schedule for sending public pillarencoded data slices to each network edge unit of the plurality ofnetwork edge units. The DS processing unit 16 facilitates partialdownloading of the target content by facilitating sending of the publicpillar encoded data slices to each network edge unit of the plurality ofnetwork edge units.

In a continuation of the example, at least one of a user device 12 and awireless user device 110 identify target content and identify publicpillars corresponding to the target content. The at least one of theuser device and the wireless user device requests a download of thepublic pillar encoded data slices from at least one of the plurality ofnetwork edge units. The at least one of the user device and wirelessuser device receives the public pillar encoded data slices of the targetcontent and stores the public pillar encoded data slices in a temporaryslice memory 118 associated with the at least one of the user device andthe wireless user device. The at least one of the user device and thewireless user device downloads corresponding private pillar encoded dataslices from at least one of the DSN memory 22 and one of the pluralityof network edge units and stores the private pillar encoded data slicesin a non-temporary slice memory 120 associated with the at least one ofthe user device and the wireless user device. The at least one of theuser device and the wireless user device moves the public pillar encodeddata slices from the temporary slice memory 118 to the non-temporaryslice memory 120. The method of operation of the computing system isdescribed in greater detail with reference to FIGS. 9A and 9B.

FIG. 9B is a flowchart illustrating an example of staging content fordownloading (pre-positioning). In particular, a method is presented foruse in conjunction with one or more functions and features described inconjunction with FIGS. 1-2, 3-9A, and also FIG. 9B.

The method begins with step 136, where processing module (e.g., adispersed storage (DS) processing unit) selects a plurality of networkedge units for staging public pillar encoded data slices. Such aselection may be based on one or more of a list of units, a unitrequest, a user device operably coupled to the unit, a geographic areaassociated with a unit, a content preference of a user device, aprevious partial download list, a new content listing message, a desiredcontent indicator of a user device, or a content selection history of auser device. For example, processing module selects a network edge unitthat is operably coupled to a user device that may require targetcontent downloading.

The method continues with step 138, where the processing moduleidentifies target content for partial download to the plurality ofnetwork edge units. Such identifying may be based on one or more of aunit request, a user device operably coupled to the unit, a contentpreference of a user device, a previous partial download list, a newcontent listing message, a desired content indicator of a user device,or a content selection history of a user device. The method continueswith step 130 of FIG. 9A, where the processing module identifies publicpillars corresponding to the target content for partial download.

The method continues at step 142, where the processing module determinesa partial downloading schedule for sending public pillar encoded dataslices, corresponding to the public pillars, to each network edge unitof the plurality of network edge units. Such a schedule may include astart time, an end time, how much of the target content to partiallydownload, a minimum download rate, an average download rate, or amaximum download rate. Such a determination may be based on one or moreof a location of the network edge unit, an availability indicator of thenetwork edge unit, a network loading indicator associated with thenetwork edge unit, and available network bandwidth associated with thenetwork edge unit, a location of a user device, an availabilityindicator of a user device associated with the network edge unit, anetwork loading indicator, historical network loading information, thetarget content, the size of the target content, a size of encoded dataslices associated with the public pillars, a user device type indicator(e.g., wireless and/or wireline), or a security requirement. Forexample, the processing module determines to start the download to anetwork edge unit, with a maximum download rate of 5 Mb per second, at11:01 PM and complete the download by 11:15 PM when the historicalnetwork loading information indicates that the network edge unittypically has more available network bandwidth in this time frame.

The method continues at step 144, where the processing modulefacilitates partial downloading of the target content by facilitatingsending of the public pillar encoded data slices to each network edgeunit of the plurality of network edge units. Such facilitation includesat least one of retrieving of the public pillar encoded data slices whenthe processing module is associated with the network edge unit andrequesting sending of the public pillar encoded data slices when theprocessing module is associated with a DS processing unit.

The method described above in conjunction with the processing module canalternatively be performed by other modules of the dispersed storagenetwork or by other computing devices. In addition, at least one memorysection (e.g., a non-transitory computer readable storage medium) thatstores operational instructions can, when executed by one or moreprocessing modules of one or more computing devices of the dispersedstorage network (DSN), cause the one or more computing devices toperform any or all of the method steps described above.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form asolid-state memory, a hard drive memory, cloud memory, thumb drive,server memory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: selecting a plurality of network edge unitsfor staging public pillar encoded data slices; identifying targetcontent for partial download to the plurality of network edge units;identifying public pillars corresponding to the target content forpartial download; determining a partial downloading schedule for sendingpublic pillar encoded data slices corresponding to the public pillars toeach network edge unit of the plurality of network edge units; andfacilitating partial downloading of the target content by facilitatingsending of the public pillar encoded data slices to each network edgeunit of the plurality of network edge units.
 2. The method of claim 1,wherein the selecting a plurality of network edge units for stagingpublic pillar encoded data slices is based on one or more of: a list ofunits, a unit request, a user device operably coupled to a unit, ageographic area associated with a unit, a content preference of a userdevice, a previous partial download list, a new content listing message,a desired content indicator of a user device, or a content selectionhistory of a user device.
 3. The method of claim 1, wherein theselecting a plurality of network edge units for staging public pillarencoded data slices includes selecting a network edge unit that isoperably coupled to a user device that requires target contentdownloading.
 4. The method of claim 1, wherein the identifying targetcontent for partial download is based on one or more of: a unit request,a user device operably coupled to a unit, a content preference of a userdevice, a previous partial download list, a new content listing message,a desired content indicator of a user device, or a content selectionhistory of a user device.
 5. The method of claim 1, wherein thedetermining a partial downloading schedule is based on one or more of: alocation of a network edge unit, an availability indicator of thenetwork edge unit, a network loading indicator associated with thenetwork edge unit, available network bandwidth associated with thenetwork edge unit, a location of a user device, an availabilityindicator of a user device associated with the network edge unit, anetwork loading indicator, historical network loading information, thetarget content, a size of the target content, a size of encoded dataslices associated with the public pillars, a user device type indicator,or a security requirement.
 6. The method of claim 1, wherein the partialdownloading schedule includes one or more of: a start time, an end time,how much of the target content to partially download, a minimum downloadrate, an average download rate, or a maximum download rate.
 7. Themethod of claim 1, wherein the identifying public pillars correspondingto the target content for partial download is based on: target content,error coding parameters, an amount of data per pillar, a securityrequirement, a performance requirement, a predetermination, a lookup, ora query.
 8. The method of claim 1, wherein the facilitating partialdownloading of the target content includes at least one of: retrievingof the public pillar encoded data slices when a processing module isassociated with the network edge units or requesting sending of thepublic pillar encoded data slices when the processing module isassociated with a DS processing unit.
 9. A computing device of a groupof computing devices of a dispersed storage network (DSN), the computingdevice comprises: an interface; a local memory; and a processing moduleoperably coupled to the interface and the local memory, wherein theprocessing module functions to: select a plurality of network edge unitsfor staging public pillar encoded data slices; identify target contentfor partial download to the plurality of network edge units; identifypublic pillars corresponding to the target content for partial download;determine a partial downloading schedule for sending public pillarencoded data slices, corresponding to the public pillars, to eachnetwork edge unit of the plurality of network edge units; and facilitatepartial downloading of the target content by facilitating sending of thepublic pillar encoded data slices to each network edge unit of theplurality of network edge units.
 10. The computing device of claim 9,wherein the select a plurality of network edge units for staging publicpillar encoded data slices is based on one or more of: a list of units,a unit request, a user device operably coupled to a unit, a geographicarea associated with a unit, a content preference of a user device, aprevious partial download list, a new content listing message, a desiredcontent indicator of a user device, or a content selection history of auser device.
 11. The computing device of claim 9, wherein the select aplurality of network edge units for staging public pillar encoded dataslices includes selecting a network edge unit that is operably coupledto a user device that requires target content downloading.
 12. Thecomputing device of claim 9, wherein the identify target content forpartial download is based on one or more of: a unit request, a userdevice operably coupled to a unit, a content preference of a userdevice, a previous partial download list, a new content listing message,a desired content indicator of a user device, or a content selectionhistory of a user device.
 13. The computing device of claim 9, whereinthe determine a partial downloading schedule is based on one or more of:a location of a network edge unit, an availability indicator of thenetwork edge unit, a network loading indicator associated with thenetwork edge unit, available network bandwidth associated with thenetwork edge unit, a location of a user device, an availabilityindicator of a user device associated with the network edge unit, anetwork loading indicator, historical network loading information, thetarget content, a size of the target content, a size of encoded dataslices associated with the public pillars, a user device type indicator,or a security requirement.
 14. The computing device of claim 9, whereinthe partial downloading schedule includes one or more of: a start time,an end time, how much of the target content to partially download, aminimum download rate, an average download rate, or a maximum downloadrate.
 15. The computing device of claim 9, wherein the facilitatepartial downloading of the target content includes at least one of:retrieving of the public pillar encoded data slices when the processingmodule is associated with the network edge units or requesting sendingof the public pillar encoded data slices when the processing module isassociated with a DS processing unit.
 16. A system including a dispersedstorage network (DSN), the system comprises: an interface; a localmemory; and a processing module operably coupled to the interface andthe local memory, wherein the processing module functions to: select aplurality of network edge units for staging public pillar encoded dataslices; identify target content for partial download to the plurality ofnetwork edge units; identify public pillars corresponding to the targetcontent for partial download; determine a partial downloading schedulefor sending public pillar encoded data slices, corresponding to thepublic pillars, to each network edge unit of the plurality of networkedge units; and facilitate partial downloading of the target content byfacilitating sending of the public pillar encoded data slices to eachnetwork edge unit of the plurality of network edge units.
 17. The systemof claim 16, wherein the select a plurality of network edge units forstaging public pillar encoded data slices is based on one or more of: alist of units, a unit request, a user device operably coupled to a unit,a geographic area associated with a unit, a content preference of a userdevice, a previous partial download list, a new content listing message,a desired content indicator of a user device, or a content selectionhistory of a user device.
 18. The system of claim 16, wherein the selecta plurality of network edge units for staging public pillar encoded dataslices includes selecting a network edge unit that is operably coupledto a user device that may require target content downloading.
 19. Thesystem of claim 16, wherein the identify target content for partialdownload is based on one or more of: a unit request, a user deviceoperably coupled to a unit, a content preference of a user device, aprevious partial download list, a new content listing message, a desiredcontent indicator of a user device, or a content selection history of auser device.
 20. The system of claim 16, wherein the facilitate partialdownloading of the target content includes at least one of: retrievingof the public pillar encoded data slices when the processing module isassociated with the network edge units or requesting sending of thepublic pillar encoded data slices when the processing module isassociated with a DS processing unit.